About Goldman Sachs

Goldman Sachs is a leading global investment banking, securities, and investment management firm providing financial services to corporations, financial institutions, governments, and individuals.

Goldman Sachs currently has 187 open roles on FindRole.

Listed pay typically runs $130,000–$250,000 across 60 roles with salary data.

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At a glance

TL;DR · AI Solutions Engineer, Associate

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As an AI Solutions Engineer at Goldman Sachs within the WM Data Engineering team, you will contribute to designing and delivering intelligent agent-based workflows and large language model (LLM)-powered applications that transform how engineers and business teams operate across the Wealth Management data ecosystem. Your day-to-day responsibilities include building and maintaining AI-powered tools integrated with cloud-native data platforms on AWS, writing well-tested code for production-quality AI components, implementing responsible AI practices, and collaborating with senior engineers and stakeholders to scope requirements and ship iteratively. You will work with technologies such as Java, Python, SQL, OpenAI APIs, LangChain frameworks, and AWS services like S3, Databricks, Snowflake, Glue, and Athena, while addressing critical issues related to data governance and financial regulation in a highly scalable environment.

Skills

Python Java SQL LLM_APIs LangChain AWS S3 Glue Databricks Snowflake Athena MWAA LangSmith RAGAS PromptFoo AI_evaluation_frameworks Responsible_AI_practices Cloud_data_services Pipeline_orchestration_tools Lakehouse_patterns

What you'll do

Build and maintain AI-powered data engineering tools integrated with the WM data platform.
Develop evaluation frameworks to measure and improve AI output quality across workloads.
Write well-tested, production-quality code for AI components with comprehensive tests.
Implement responsible AI practices including PII handling and audit logging.
Create backend services and APIs exposing AI-driven data tooling for internal use.

What we're looking for

3+ years of software engineering experience with AI application development
Proficiency in Java, Python, SQL, and hands-on LLM API experience
Understanding of ETL/ELT pipelines, data warehousing, and cloud data services
Familiarity with responsible AI practices including prompt injection defenses
Experience building and maintaining backend services for AI-driven tooling
Strong analytical skills and effective communication abilities